Pathogenic microorganisms produce numerous metabolites, including volatile organic compounds (VOCs). Monitoring these metabolites in biological matrices (e.g., urine, blood, or breath) can reveal the presence of specific microorganisms, enabling the early diagnosis of infections and the timely implementation of targeted therapy. However, complex matrices only contain trace levels of VOCs, and their constituent components can hinder determination of these compounds. Therefore, modern analytical techniques enabling the non-invasive identification and precise quantification of microbial VOCs are needed. In this paper, we discuss bacterial VOC analysis under in vitro conditions, in animal models and disease diagnosis in humans, including techniques for offline and online analysis in clinical settings. We also consider the advantages and limitations of novel microextraction techniques used to prepare biological samples for VOC analysis, in addition to reviewing current clinical studies on bacterial volatilomes that address inter-species interactions, the kinetics of VOC metabolism, and species- and drug-resistance specificity.

Volatile organic compounds (VOCs) have been proposed in the last two decades as biomarkers for disease detection and therapeutic monitoring. Model in vitro experiments with established cell lines are fundamental to clarify whether given VOCs originate from normal human cells or pathogens, including transformed cancer cells. Due to the trace concentrations of target metabolites, adsorptive enrichment is needed before gas chromatography-mass spectrometry (GC-MS) analysis, with solid-phase microextraction (SPME) being perfectly suited for this purpose. Here, a modification of SPME, the thin-film microextraction (TFME) technique, is proposed for analysis of cellular VOCs, which utilizes a planar mesh coated with stationary phase to increase the extraction phase volume and active surface area. In this study, four different adsorbents were compared: carboxen, divinylbenzene, hydrophobic−lipophilic balanced and polydimethylsiloxane. Amongst them, HLB sheets using poly(divinylbenzene-co-N-vinyl-pyrrolidone) skeleton structure proved to be the most versatile, enabling the most sensitive analysis of VOCs with a broad polarity and volatility. For HLB, sampling type (internal static headspace, external bi-directional headspace), extraction temperature and extraction time were also examined. An established method was successfully applied to analyze metabolites produced by A549 cells revealing five volatiles at significantly higher (additionally benzaldehyde at lower) levels in cell culture medium compared to the cell-free reference medium headspace.

Bacterial infection of the lower respiratory tract frequently occurs in mechanically ventilated patients and may develop into life-threatening conditions. Yet, existing diagnostic methods have moderate sensitivity and specificity, which results in the overuse of broad-spectrum antibiotics administered prophylactically. This study aims to evaluate the suitability of volatile bacterial metabolites for the breath-based test, which is used for diagnosing Ventilator-Associated Pneumonia (VAP). The in vitro experiments with pathogenic bacteria most prevalent in VAP etiology (i.e., Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa) were performed to identify bacteria-derived metabolites using a specially designed cultivation system enabling headspace sampling for GC-MS analysis. Thirty-nine compounds were found to be significantly metabolized by tested species and, therefore, selected for monitoring in the exhaled breath of critically ill, mechanically ventilated (MV) patients. The emission of volatiles from medical respiratory devices was investigated to estimate the risk of spoiling breath results with exogenous pollutants. Bacterial metabolites were then evaluated to differentiate VAP patients from non-infected MV controls using Receiver Operating Characteristic (ROC) analysis, with AUC, sensitivity, and specificity calculated. Nine bacterial metabolites that passed verification through a non-parametric ANOVA test for significance and LASSO penalization were identified as key discriminators between VAP and non-VAP patients. The diagnostic model achieved an AUC of 0.893, with sensitivity and specificity values of 87% and 82.4%, respectively, being competitive with traditional methods. Further validation could solidify its clinical utility in critical care settings.

β-Lactam antibiotics are most commonly used in the critically ill, but their effective dosing is challenging and may result in sub-therapeutic concentrations that can lead to therapy failure and even promote antimicrobial resistance. In this study, we present the analytical tool enabling specific and sensitive determination of the sole biologically active fraction of piperacillin and imipenem in biological material from the critically ill. Thin-film microextraction sampling technique, followed by rapid liquid chromatography–tandem mass spectrometry (LC-MS/MS) analysis, was optimized and validated for the quantitative determination of antibiotics in blood and bronchoalveolar lavage (BAL) specimens collected from intensive care unit (ICU) patients suffering from ventilation-associated pneumonia (n = 18 and n = 9, respectively). The method was optimized and proved to meet the criteria of US Food and Drug Administration (FDA) guidelines for bioanalytical method validation. Highly selective, sensitive, accurate and precise analysis by means of thin-film microextraction–LC-MS/MS, which is not affected by matrix-related factors, was successfully applied in clinical settings, revealing poor penetration of piperacillin and imipenem from blood into BAL fluid (reflecting the site of bacterial infection), nonlinearity in antibiotic binding to plasma-proteins and drug-specific dependence on creatinine clearance. This work demonstrates that only a small fraction of biologically active antibiotics reach the site of infection, providing clinicians with a high-throughput analytical tool for future studies on personalized therapeutic drug monitoring when tailoring the dosing strategy to an individual patient.

Current diagnostic methods for bacterial infections in critically ill patients, including ventilator-associated pneumonia (VAP), are time-consuming, while empirical antibiotic therapy contributes to rising resistance. Bacteria-derived volatile organic compounds (VOCs) are being explored as specific biomarkers for pathogen identification and treatment monitoring. This study expands knowledge of Escherichia coli metabolism by identifying VOCs produced by both multidrug-resistant and susceptible strains, characterizing their temporal profiles during growth, and assessing VOC profile changes after imipenem exposure. Reference strains and 21 clinical isolates (derived from BAL samples of VAP patients) were cultured under controlled conditions. Headspace VOCs were preconcentrated using multibed sorption tubes and analyzed by gas chromatography–mass spectrometry (GC-MS), with compound identities confirmed using external standards. Sampling at seven time points over 24 h cultures revealed three VOC emission patterns: continuous release, temporary maximum, and compound uptake. In total, 57 VOCs were identified from the susceptible strain and 41 from the resistant one, with dimethyl disulfide, 2-butenal, ethyl acetate, and furan elevated in the resistant strain. Imipenem addition altered VOC production in the susceptible strain, with levels of six compounds elevated and seven reduced, while resistant profiles remained stable. Clinical isolates produced 71 VOCs, showing greater metabolic diversity and highlighting the relevance of isolate-derived VOCs in future studies.

Bacterial infection of the lower respiratory tract frequently occurs in mechanically ventilated pa-tients and may develop into life-threatening conditions. Yet existing diagnostic methods have moderate sensitivity and specificity, which results in the overuse of broad-spectrum antibiotics administrated prophylactically. This study aims to evaluate the suitability of volatile bacterial me-tabolites for breath-based test diagnosing Ventilation-Associated Pneumonia (VAP). The in vitro experiments with pathogenic microorganisms most prevalent in VAP patients (i.e., Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa) were performed to identify bacteria-derived metabolites using specially designed cultivation system enabling headspace sam-pling for GC-MS analysis. Thirty-nine compounds were found to be significantly metabolized by tested species and, therefore, selected for monitoring in the exhaled breath of critically ill, me-chanically ventilated (MV) patients. The emission of volatiles from medical respiratory devices was investigated to estimate the risk of spoiling breath results with exogenous pollutants. Bacterial metabolites were then evaluated to differentiate VAP patients from non-infected MV controls using receiver operating characteristic (ROC) analysis, with AUC, sensitivity, and specificity calculated. Nine bacterial metabolites that passed verification through a non-parametric ANOVA test for significance and LASSO penalization were identified as key discriminators between VAP and non-VAP patients. The diagnostic model achieved an AUC of 0.893, with sensitivity and specificity values of 87% and 82.4%, respectively, being competitive with traditional methods. Further vali-dation could solidify its clinical utility in critical care settings.